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Identity Forge MCP

Identity Forge MCP

Official
by KasayoDotCom
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Persist externally researched name candidates

add_name_candidates

Keep shortlists out of chat transcripts by persisting 1-50 name candidates to a project board, with UUID-based safe retries and no AI credits.

Instructions

Persist 1-50 names your own agent, another model, or manual research produced onto the durable project board, so a shortlist never lives only in the chat transcript. This is the free counterpart to generate_names: it stores names rather than authoring them, and spends no AI credits. Each item needs a caller-generated UUID, which makes retries safe. Sending identical data again returns the same row; reusing an id with changed data returns a conflict instead of silently overwriting. Requires the naming:write scope.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "projectId": "<projectId>",
      "candidates": "<candidates>"
    },
    "name": "add_name_candidates"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectIdYesOwned naming project id from list_naming_projects.
candidatesYes1-50 candidates to persist.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses idempotency semantics ('identical data again returns the same row; reusing an id with changed data returns a conflict'), the required 'naming:write scope,' and that it 'spends no AI credits.' This is rich behavioral context beyond what annotations could provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is four sentences, each adding value: purpose, relationship to generate_names, idempotency behavior, and auth requirement. There is no filler or repetition of schema fields, making it appropriately sized and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the tool's purpose, usage context, idempotency, and auth requirement, which is sufficient for an agent to select and invoke it. However, with no output schema, it could optionally elaborate on the success response format beyond conflict/duplicate cases, so I score 4 rather than 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds meaningful semantics for the candidateId parameter by explaining duplicate vs conflict behavior in concrete terms, which is not fully captured in the schema's brief idempotency note. This extra detail justifies a 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'persist' and clearly identifies the resource ('names...onto the durable project board'). It distinguishes from sibling generate_names by stating it 'stores names rather than authoring them,' which satisfies sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly positions this tool as 'the free counterpart to generate_names,' clarifying when to use it (when names are already produced) versus when to use generate_names (authoring new names). This gives the agent clear guidance on selecting the correct tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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